The dynamics and geometry of choice in the premotor cortex

• 成果类型: Article
• 署名作者: Genkin, Mikhail; Shenoy, Krishna V.; Chandrasekaran, Chandramouli; Engel, Tatiana A.
• 署名单位: Cold Spring Harbor Laboratory; Stanford University; Howard Hughes Medical Institute; Stanford University; Boston University; Boston University; Boston University; Boston University; Princeton University
• 刊物名称: Nature
• ISSN/ISSBN: 0028-3391
• DOI: 10.1038/s41586-025-09199-1
• 发表日期: 2025-09-04
• 关键词: neural dynamics; dimensionality; computation

摘要

The brain represents sensory variables in the coordinated activity of neural populations, in which tuning curves of single neurons define the geometry of the population code1,2. Whether the same coding principle holds for dynamic cognitive variables remains unknown because internal cognitive processes unfold with a unique time course on single trials observed only in the irregular spiking of heterogeneous neural populations3, 4, 5, 6, 7-8. Here we show the existence of such a population code for the dynamics of choice formation in the primate premotor cortex. We developed an approach to simultaneously infer population dynamics and tuning functions of single neurons to the population state. Applied to spike data recorded during decision-making, our model revealed that populations of neurons encoded the same dynamic variable predicting choices, and heterogeneous firing rates resulted from the diverse tuning of single neurons to this decision variable. The inferred dynamics indicated an attractor mechanism for decision computation. Our results reveal a unifying geometric principle for neural encoding of sensory and dynamic cognitive variables.